Distances API Example¶

Run this example in Colab¶

Setup¶

Install the Signal Ocean SDK:

pip install signal-ocean

Set your subscription key acquired here: https://apis.signalocean.com/profile

In [1]:

pip install signal-ocean

pip install signal-ocean

In [2]:

signal_ocean_api_key = '' #replace with your subscription key

signal_ocean_api_key = '' #replace with your subscription key

Calculate a distance over 2 ports¶

Create a connections towards distances API. Then call the distance API to get a distance between Fuijairah and Singapore for a VLCC vessel (corresponding restrictions applied)

In [3]:

from signal_ocean import Connection
from signal_ocean.distances import DistancesAPI, VesselClassFilter, PortFilter, LoadingCondition

connection = Connection(api_key=signal_ocean_api_key)
distances_api = DistancesAPI(connection)

load_port = distances_api.get_ports(PortFilter(name_like='Fujairah'))[0]
discharge_port = distances_api.get_ports(PortFilter(name_like='Singapore'))[0]

vessel_class = distances_api.get_vessel_classes(VesselClassFilter(name_like='vlcc'))[0]
distanceInNM = distances_api.get_port_to_port_distance(vessel_class, LoadingCondition.BALLAST, load_port, discharge_port)

print(distanceInNM)

from signal_ocean import Connection from signal_ocean.distances import DistancesAPI, VesselClassFilter, PortFilter, LoadingCondition connection = Connection(api_key=signal_ocean_api_key) distances_api = DistancesAPI(connection) load_port = distances_api.get_ports(PortFilter(name_like='Fujairah'))[0] discharge_port = distances_api.get_ports(PortFilter(name_like='Singapore'))[0] vessel_class = distances_api.get_vessel_classes(VesselClassFilter(name_like='vlcc'))[0] distanceInNM = distances_api.get_port_to_port_distance(vessel_class, LoadingCondition.BALLAST, load_port, discharge_port) print(distanceInNM)

3302.86

Create a distance matrix¶

Find distance in NM for a Aframax vessel from Trieste to every available port. Persist the output in an excel file.

In [4]:

distancesFromTriesteDictionary = {}

port_from = distances_api.get_ports(PortFilter(name_like='Trieste'))[0]
ports_to_get_distance = ['Rotterdam','Singapore','Lome','Long Beach','Galveston','Pazflor','Bonny','Ras Tanura','Houston','Escravos']

for port_to_filter in ports_to_get_distance:
    port_to = distances_api.get_ports(PortFilter(name_like=port_to_filter))[0]
    distanceInNM = distances_api.get_port_to_port_distance(vessel_class, LoadingCondition.BALLAST, port_from, port_to)
    distancesFromTriesteDictionary[port_to.name] = float(distanceInNM)

distancesFromTriesteDictionary = {} port_from = distances_api.get_ports(PortFilter(name_like='Trieste'))[0] ports_to_get_distance = ['Rotterdam','Singapore','Lome','Long Beach','Galveston','Pazflor','Bonny','Ras Tanura','Houston','Escravos'] for port_to_filter in ports_to_get_distance: port_to = distances_api.get_ports(PortFilter(name_like=port_to_filter))[0] distanceInNM = distances_api.get_port_to_port_distance(vessel_class, LoadingCondition.BALLAST, port_from, port_to) distancesFromTriesteDictionary[port_to.name] = float(distanceInNM)

In [5]:

import pandas as pd
import openpyxl

df = pd.DataFrame(data=distancesFromTriesteDictionary, index=[0])
pd.options.display.float_format = '{:,.2f}'.format
df = (df.T)
df.to_excel('simpleDistanceMatrix_Trieste_Aframax_Ballast.xlsx')
df

import pandas as pd import openpyxl df = pd.DataFrame(data=distancesFromTriesteDictionary, index=[0]) pd.options.display.float_format = '{:,.2f}'.format df = (df.T) df.to_excel('simpleDistanceMatrix_Trieste_Aframax_Ballast.xlsx') df

Out[5]:

	0
Rotterdam	3,079.19
Singapore	6,386.87
Lome	4,688.84
Long Beach	13,980.85
Galveston	6,403.92
Pazflor	5,500.45
Bonny	5,027.66
Ras Tanura	4,480.52
Houston	6,430.57
Escravos	4,884.11